A geometric framework for stop sign detection. - Qi Li 001; Gongbo Liang; Yongyi Gong (ChinaSIP, 2015)

Pedestrian detection via a leg-driven physiology framework. - Gongbo Liang; Qi Li 001; Xiangui Kang (ICIP, 2016)

Enhancing Radiomic Features of CT Images using Generative Adversarial Network with Alternative Improvement. - Gongbo Liang; Jie Zhang 092; Michael A. Brooks; Jessica Howard; Jin Chen 004 (AMIA, 2018)

Joint 2D-3D Breast Cancer Classification. - Gongbo Liang; Xiaoqin Wang; Yu Zhang 094; Xin Xing 002; Hunter Blanton; Tawfiq Salem; Nathan Jacobs (BIBM, 2019)

2D Convolutional Neural Networks for 3D Digital Breast Tomosynthesis Classification. - Yu Zhang 094; Xiaoqin Wang; Hunter Blanton; Gongbo Liang; Xin Xing 002; Nathan Jacobs (BIBM, 2019)

Defense-PointNet: Protecting PointNet Against Adversarial Attacks. - Yu Zhang 094; Gongbo Liang; Tawfiq Salem; Nathan Jacobs (IEEE BigData, 2019)

GANai: Standardizing CT Images using Generative Adversarial Network with Alternative Improvement. - Gongbo Liang; Sajjad Fouladvand; Jie Zhang 092; Michael A. Brooks; Nathan Jacobs; Jin Chen 004 (ICHI, 2019)

Improved Trainable Calibration Method for Neural Networks. - Gongbo Liang; Yu Zhang 094; Xiaoqin Wang; Nathan Jacobs (BMVC, 2020)

Dynamic Image for 3D MRI Image Alzheimer's Disease Classification. - Xin Xing 002; Gongbo Liang; Hunter Blanton; Muhammad Usman Rafique; Chris Wang; Ai-Ling Lin; Nathan Jacobs (ECCV Workshops (1), 2020)

Weakly-Supervised Self-Training for Breast Cancer Localization*. - Gongbo Liang; Xiaoqin Wang; Yu Zhang 094; Nathan Jacobs (EMBC, 2020)

Multi-Branch Attention Networks for Classifying Galaxy Clusters. - Yu Zhang 094; Gongbo Liang; Yuanyuan Su; Nathan Jacobs (ICPR, 2020)

Unsupervised Domain Adaptation for Mammogram Image Classification: A Promising Tool for Model Generalization. - Yu Zhang 094; Gongbo Liang; Nathan Jacobs; Xiaoqin Wang (CoRR, 2020)

Improved Trainable Calibration Method for Neural Networks on Medical Imaging Classification. - Gongbo Liang; Yu Zhang 094; Xiaoqin Wang; Nathan Jacobs (CoRR, 2020)

Weakly-Supervised Feature Learning via Text and Image Matching. - Gongbo Liang; Connor Greenwell; Yu Zhang 094; Xiaoqin Wang; Ramakanth Kavuluru; Nathan Jacobs (CoRR, 2020)

Optical Wavelength Guided Self-Supervised Feature Learning For Galaxy Cluster Richness Estimate. - Gongbo Liang; Yuanyuan Su; Sheng-Chieh Lin; Yu Zhang 094; Yuanyuan Zhang; Nathan Jacobs (CoRR, 2020)

Dynamic Feature Alignment for Semi-supervised Domain Adaptation. - Yu Zhang 094; Gongbo Liang; Nathan Jacobs (BMVC, 2021)

Alzheimer's Disease Classification Using 2D Convolutional Neural Networks. - Gongbo Liang; Xin Xing 002; Liangliang Liu 001; Yu Zhang 094; Qi Ying; Ai-Ling Lin; Nathan Jacobs (EMBC, 2021)

Multi-Modal Data Analysis for Alzheimer's Disease Diagnosis: An Ensemble Model Using Imagery and Genetic Features. - Qi Ying; Xin Xing 002; Liangliang Liu 001; Ai-Ling Lin; Nathan Jacobs; Gongbo Liang (EMBC, 2021)

Beware the Black-Box of Medical Image Generation: an Uncertainty Analysis by the Learned Feature Space. - Yunni Qu; David Yan; Eric Xing; Fengbo Zheng; Jie Zhang 092; Liangliang Liu 001; Gongbo Liang (EMBC, 2022)

Neural Network Decision-Making Criteria Consistency Analysis via Inputs Sensitivity. - Eric Xing; Liangliang Liu 001; Xin Xing 002; Yunni Qu; Nathan Jacobs; Gongbo Liang (ICPR, 2022)

Advit: Vision Transformer On Multi-Modality Pet Images For Alzheimer Disease Diagnosis. - Xin Xing 002; Gongbo Liang; Yu Zhang 094; Subash Khanal; Ai-Ling Lin; Nathan Jacobs (ISBI, 2022)

Development of CNN models for the enteral feeding tube positioning assessment on a small scale data set. - Gongbo Liang; Halemane Ganesh; Dylan Steffe; Liangliang Liu 001; Nathan Jacobs; Jie Zhang 092 (BMC Medical Imaging, 2022)

Benchmark Assessment for DeepSpeed Optimization Library. - Gongbo Liang; Izzat Alsmadi (CoRR, 2022)

A Mutation-based Text Generation for Adversarial Machine Learning Applications. - Jesus Guerrero; Gongbo Liang; Izzat Alsmadi (CoRR, 2022)

LLRHNet: Multiple Lesions Segmentation Using Local-Long Range Features. - Liangliang Liu 001; Ying Wang; Jing Chang; Pei Zhang; Gongbo Liang; Hui Zhang (Frontiers Neuroinformatics, 2022)

Contrastive Cross-Modal Pre-Training: A General Strategy for Small Sample Medical Imaging. - Gongbo Liang; Connor Greenwell; Yu Zhang 094; Xin Xing 002; Xiaoqin Wang; Ramakanth Kavuluru; Nathan Jacobs (IEEE J. Biomed. Health Informatics, 2022)

Mutation-Based Adversarial Attacks on Neural Text Detectors. - Gongbo Liang; Jesus Guerrero; Izzat Alsmadi (CoRR, 2023)

A spatiotemporal correlation deep learning network for brain penumbra disease. - Liangliang Liu 001; Pei Zhang; Gongbo Liang; Shufeng Xiong; Jianxin Wang 001; Guang Zheng (Neurocomputing, 2023)

Simulated Quantum Mechanics-Based Joint Learning Network for Stroke Lesion Segmentation and TICI Grading. - Liangliang Liu 001; Jing Chang; Gongbo Liang; Shufeng Xiong (IEEE J. Biomed. Health Informatics, 2023)

Enhancing Machine Learning Based SQL Injection Detection Using Contextualized Word Embedding. - Janet Zulu; Bonian Han; Izzat Alsmadi; Gongbo Liang (ACM Southeast Regional Conference, 2024)

Improving Medical Imaging Model Calibration through Probabilistic Embedding. - Bonian Han; Yuktha Priya Masupalli; Xin Xing 002; Gongbo Liang (IEEE Big Data, 2024)

Multi-Scale Self-Supervised Consistency Training for Trustworthy Medical Imaging Classification. - Bonian Han; Cristian Moran; Jeong Yang; Young Lee 002; Zechun Cao; Gongbo Liang (EMBC, 2024)

Analyzing the Usability, Performance, and Cost-Efficiency of Deploying ML Models on BigQuery ML and Vertex AI in Google Cloud. - Hongyu Wang; Jeong Yang; Gongbo Liang; Young Lee 002; Zechun Cao (ICCBDC, 2024)

Interactive Learning Modules for Fostering Secure Coding Proficiency in Introductory Programming Courses. - Guangming Xing; Gongbo Liang; Tawfiq Salem (SIGCSE (2), 2024)

LEARNDB: A Comprehensive Toolkit for Database Education. - Guangming Xing; Tawfiq Salem; Gongbo Liang (SIGCSE (2), 2024)

Using Large Language Models in Public Transit Systems, San Antonio as a case study. - Ramya Jonnala; Gongbo Liang; Jeong Yang; Izzat Alsmadi (CoRR, 2024)

Unveiling Roadway Hazards: Enhancing Fatal Crash Risk Estimation Through Multiscale Satellite Imagery and Self-Supervised Cross-Matching. - Gongbo Liang; Janet Zulu; Xin Xing 002; Nathan Jacobs (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

Benchmark assessment for the DeepSpeed acceleration library on image classification. - Gongbo Liang; Mohammed Salem Atoum; Xin Xing 002; Izzat Alsmadi (Clust. Comput., 2024)

H-Net: Heterogeneous Neural Network for Multi-Classification of Neuropsychiatric Disorders. - Liangliang Liu 001; Jinpu Xie; Jing Chang; Zhihong Liu; Tong Sun; Hongbo Qiao; Gongbo Liang; Wei Guo 029 (IEEE J. Biomed. Health Informatics, 2024)

PortrAid: An AI-Driven Portrait Assistant for Professional-Quality Image Composition. - Jaspal Singh Kahlon; Gongbo Liang (ACM Southeast Regional Conference, 2025)

ChartCode: A Flowchart-Based Tool for Introductory Programming Courses. - Guangming Xing; Tawfiq Salem; Gongbo Liang (SIGCSE (2), 2025)

Measuring and Improving the Efficiency of Python Code Generated by LLMs Using CoT Prompting and Fine-Tuning. - Ramya Jonnala; Jeong Yang; Young Lee 002; Gongbo Liang; Zechun Cao (IEEE Access, 2025)

Exploring the Potential of Large Language Models in Public Transportation: San Antonio Case Study. - Ramya Jonnala; Gongbo Liang; Jeong Yang; Izzat Alsmadi (CoRR, 2025)

Benchmarking Robustness of Contrastive Learning Models for Medical Image-Report Retrieval. - Demetrio Deanda; Yuktha Priya Masupalli; Jeong Yang; Young Lee 002; Zechun Cao; Gongbo Liang (CoRR, 2025)

Defending mutation-based adversarial text perturbation: a black-box approach. - Demetrio Deanda; Izzat Alsmadi; Jesus Guerrero; Gongbo Liang (Clust. Comput., 2025)

Can Contrastive Learning Improve Class-Imbalanced Diffusion Model? - Fang Chen; Alex Villa; Gongbo Liang; Xiaoyi Lu; Meng Tang (CoRR, 2025)